Abstract: The use of CT scans has recently increased, for example, in virtual colonoscopy, CT cardiac screening, screening of the lung in smokers, whole-body CT in asymptomatic patients, and CT imaging of children. Shortening of the scanning time to around 1 second, eliminating the strict need for the subject to remain still or be sedated, is one of the main reasons for the large increase in the pediatric population. CT scans of children have been estimated to produce non-negligible increases in the probability of lifetime cancer mortality, leading to calls for the use of reduced current settings for CT scans of children. For these reasons, the CT industry has put in a lot of effort to develop low-dose CT. One active area of research is methods to reduce the radiation counts by applying adaptive collimation to block unnecessary x-ray photons. Another active area of research is the development of more robust image reconstruction algorithms that are less sensitive to noise for low-count data. This grant proposal is focused on the second approach ? development of fast and robust reconstruction algorithms. It is known that some iterative image reconstruction algorithms outperform the analytical filtered backprojection (FBP) algorithm in terms of producing less-noisy images with the same data set. One disadvantage of these iterative algorithms is their long computation time, making them impractical in a real- world CT reconstruction tasks. For this reason, the FBP algorithm is still the main work horse for CT applications. The main goal of the proposed research is to develop fast and robust iterative-algorithms so that their computation time is at the same order of an analytic FBP algorithm, using experimental low-dose phantom, cadaver data, and low-dose cancer screen chest CT patient data to perform comparison studies. We will answer the question: When the fast and robust algorithms are used, how much can the CT dose be reduced while retaining the image quality of a standard-dose CT produced by the conventional FBP? This R15 project provides Weber State University (WSU) computer engineering and computer science students with hands-on opportunities and experiences of performing real-world research in the field of healthcare. It will stimulate the interests of students so that they consider a career in biomedical and bioengineering field/industry.